Consequences of Long-Distance Dispersal for Epidemic Spread: Patterns, Scaling, and Mitigation.

Epidemics caused by long-distance dispersed pathogens result in some of the most explosive and difficult to control diseases of both plants and animals (including humans). Yet the factors influencing disease spread, especially in the early stages of the outbreak, are not well-understood. We present scaling relationships, of potentially widespread relevance, that were developed from more than 15 years of field and in silico single focus studies of wheat stripe rust spread. These relationships emerged as a consequence of accounting for a greater proportion of the fat-tailed disease gradient that may be frequently underestimated in disease spread studies. Leptokurtic dispersal gradients (highly peaked and fat-tailed) are relatively common in nature and they can be represented by power law functions. Power law scale invariance properties generate patterns that repeat over multiple spatial scales, suggesting important and predictable scaling relationships between disease levels during the first generation of disease outbreaks and subsequent epidemic spread. Experimental wheat stripe rust outbreaks and disease spread simulations support theoretical scaling relationships from power law properties and suggest that relatively straightforward scaling approximations may be useful for projecting the spread of disease caused by long-distance dispersed pathogens. Our results suggest that, when actual dispersal/disease data are lacking, an inverse power law with exponent = 2 may provide a reasonable approximation for modeling disease spread. Furthermore, our experiments and simulations strongly suggest that early control treatments with small spatial extent are likely to be more effective at suppressing an outbreak caused by a long-distance dispersed pathogen than would delayed treatment of a larger area. The scaling relationships we detail and the associated consequences for disease control may be broadly applicable to plant and animal pathogens characterized by non-exponentially bound, fat-tailed dispersal gradients.

Variable competitive effects of fungicide resistance in field experiments with a plant pathogenic fungus.

Classic evolutionary theory suggests that mutations associated with antimicrobial and pesticide resistance result in a fitness cost in the absence of the selective antimicrobial agent or pesticide. There is experimental evidence to support fitness costs associated with resistance to anti-microbial compounds and pesticides across many biological disciplines, including human pathology, entomology, plant sciences, and plant pathology. However, researchers have also found examples of neutral and increased fitness associated with resistance, where the effect of a given resistance mutation depends on environmental and biological factors. We used Zymoseptoria tritici, a model evolutionary plant pathogenic fungus, to compare the competitive ability of fungicide-resistant isolates to fungicide-sensitive isolates. We conducted four large-scale inoculated winter wheat experiments at Oregon State University agriculture experiment stations. We found a significant change in the frequency of fungicide resistance over time in all four experiments. The direction and magnitude of these changes, however, differed by experimental location, year of experiment, and inoculum resistance treatment (fungicide-resistant, resistant/sensitive mixture, and fungicide-sensitive). These results suggest that the competitive ability of resistant isolates relative to sensitive isolates varied depending upon environmental conditions, including the initial frequency of resistant individuals in the population.

Evidence of Selection for Fungicide Resistance in Zymoseptoria tritici Populations on Wheat in Western Oregon.

Plant pathogens pose a major challenge to maintaining food security in many parts of the world. Where major plant pathogens are fungal, fungicide resistance can often thwart regional control efforts. Zymoseptoria tritici, causal agent of Septoria tritici blotch, is a major fungal pathogen of wheat that has evolved resistance to chemical control products in four fungicide classes in Europe. Compared with Europe, however, fungicide use has been less and studies of fungicide resistance have been infrequent in North American Z. tritici populations. Here, we confirm first reports of Z. tritici fungicide resistance evolution in western Oregon through analysis of the effects of spray applications of propiconazole and an azoxystrobin + propiconazole mixture during a single growing season. Frequencies of strobilurin-resistant isolates, quantified as proportions of G143A mutants, were significantly higher in azoxystrobin-sprayed plots compared with plots with no azoxystrobin treatment at two different locations and were significantly higher in plots of a moderately resistant cultivar than in plots of a susceptible cultivar. Thus, it appears that western Oregon Z. tritici populations have the potential to evolve levels of strobilurin resistance similar to those observed in Europe. Although the concentration of propiconazole required to reduce pathogen growth by 50% values were numerically greater for isolates collected from plots receiving propiconazole than in control plots, this effect was not significant (P > 0.05).

Degree of host susceptibility in the initial disease outbreak influences subsequent epidemic spread.

Disease epidemics typically begin as an outbreak of a relatively small, spatially explicit population of infected individuals (focus), in which disease prevalence increases and rapidly spreads into the uninfected, at-risk population. Studies of epidemic spread typically address factors influencing disease spread through the at-risk population, but the initial outbreak may strongly influence spread of the subsequent epidemic.We initiated wheat stripe rust Puccinia striiformis f. sp. tritici epidemics to assess the influence of the focus on final disease prevalence when the degree of disease susceptibility differed between the at-risk and focus populations.When the focus/at-risk plantings consisted of partially genetic resistant and susceptible cultivars, final disease prevalence was statistically indistinguishable from epidemics produced by the focus cultivar in monoculture. In these experimental epidemics, disease prevalence was not influenced by the transition into an at-risk population that differed in disease susceptibility. Instead, the focus appeared to exert a dominant influence on the subsequent epidemic.Final disease prevalence was not consistently attributable to either the focus or the at-risk population when focus/at-risk populations were planted in a factorial set-up with a mixture (~28% susceptible and 72% resistant) and susceptible individuals. In these experimental epidemics, spatial heterogeneity in disease susceptibility within the at-risk population appeared to counter the dominant influence of the focus.Cessation of spore production from the focus (through fungicide/glyphosate application) after 1.3 generations of stripe rust spread did not reduce final disease prevalence, indicating that the focus influence on disease spread is established early in the epidemic.Synthesis and applications. Our experiments indicated that outbreak conditions can be highly influential on epidemic spread, even when disease resistance in the at-risk population is greater than that of the focus. Disease control treatments administered shortly after the initial outbreak within the focus may either prevent an epidemic from occurring or reduce its severity.

Influential disease foci in epidemics and underlying mechanisms: a field experiment and simulations.

Pathogen invasions pose a growing threat to ecosystem stability and public health. Guidelines for the timing and spatial extent of control measures for pathogen invasions are currently limited, however. We conducted a field experiment using wheat (Triticum aestivum) stripe rust, caused by the wind-dispersed fungus Puccinia striiformis, to study the extent to which host heterogeneity in an initial outbreak focus influences subsequent disease spread. We varied the frequency of susceptible host plants in an initial outbreak focus and in the non-focus of experimental plots, and observed the progress of epidemics produced by artificial inoculation. The frequency of susceptible hosts in the initial outbreak focus increased the spread of stripe rust in the experimental plots, while frequency of susceptible hosts outside the initial outbreak focus did not. This suggests that factors influencing pathogen reproduction in the initial outbreak focus are key to the control of epidemics of stripe rust. Two mechanisms may underlie the field results. The first is the continuing, direct infection of susceptible hosts in areas outside the initial outbreak focus by disease propagules arriving from the initial outbreak focus. The second is highly local proliferation of disease caused by direct descendants of colonizing individuals originating from the initial outbreak focus. We considered these two alternatives in simulations of a generalized pathogen exhibiting fat-tailed dispersal, similar to P. striiformis. Simulations showed a dominant effect of conditions in the initial outbreak focus, in agreement with the field experiment, but indicated that, over time, this dominance may erode. Analysis of the duration of focal dominance led to the conclusion that both mechanisms contribute to the phenomenon of focal dominance, and that the frequency of susceptible hosts in the initial outbreak focus had a stronger influence when the proportion of propagules that remained local during dispersal was higher. Overall, our results suggest that targeting pathogen reproduction in the initial outbreak focus will have a disproportionately large impact on subsequent epidemic spread.

Spatial scaling relationships for spread of disease caused by a wind-dispersed plant pathogen.

Spatial scale is of great importance to understanding the spread of organisms exhibiting long-distance dispersal (LDD). We tested whether epidemics spread in direct proportion to the size of the host population and size of the initial disease focus. This was done through analysis of a previous study of the effects of landscape heterogeneity variables on the spread of accelerating epidemics of wheat (Triticum aestivum) stripe rust, caused by the fungus Puccinia striiformis f. sp. tritici. End-of-season disease gradients were constructed by estimating disease prevalence at regular distances from artificially inoculated foci of different sizes, in field plots of different dimensions. In one set of comparisons, all linear dimensions (plot width and length, focus width and length, and distance between observation points) differed by a factor of four. Disease spread was substantially greater in large plot/large focus treatments than in small plot/small focus treatments. However, when disease gradients were plotted using focus width as the unit distance, they were found to be highly similar, suggesting a proportional relationship between focus or plot size and disease spread. A similar relationship held when comparing same-size plots inoculated with different-sized foci, an indication that focus size is the driver of this proportionality. Our results suggest that power law dispersal of LDD organisms results in scale-invariant relationships, which are useful for better understanding spatial spread of biological invasions, extrapolating results from small-scale experiments to invasions spreading over larger scales, and predicting speed and pattern of spread as an invasion expands.

Landscape heterogeneity and disease spread: experimental approaches with a plant pathogen.

Understanding landscape effects on disease spread can contribute to the prediction and control of epidemic invasions. We conducted large-scale field experiments with wheat stripe rust, which is caused by a wind-dispersed rust fungus. Three landscape heterogeneity variables were altered: host frequency (mixtures of susceptible and resistant plants), host patch size (different plot sizes), and size of initial disease focus (attained by artificial inoculation). Assessments of disease prevalence at different distances from the disease foci were used to quantify effects of landscape variables. We expected that a low frequency of susceptible hosts, small host patch sizes, and small initial disease foci would reduce secondary inoculum levels and thus suppress disease spread. Low host frequency and small initial disease foci greatly reduced epidemic spread. We did not detect an effect of host patch size on disease spread, though artificial inoculations did not allow us to measure the potential for small patches to escape infection under conditions of random deposition of initial inoculum. Our results suggest that, for diseases epidemiologically similar to wheat stripe rust, epidemic invasions may be suppressed by decreasing host frequency, limiting the size of initial outbreak foci, and applying control measures soon after epidemic establishment.

Long-distance dispersal and accelerating waves of disease: empirical relationships.

Classic approaches to modeling biological invasions predict a "traveling wave" of constant velocity determined by the invading organism's reproductive capacity, generation time, and dispersal ability. Traveling wave models may not apply, however, for organisms that exhibit long-distance dispersal. Here we use simple empirical relationships for accelerating waves, based on inverse power law dispersal, and apply them to diseases caused by pathogens that are wind dispersed or vectored by birds: the within-season spread of a plant disease at spatial scales of <100 m in experimental plots, historical plant disease epidemics at the continental scale, the unexpectedly rapid spread of West Nile virus across North America, and the transcontinental spread of avian influenza strain H5N1 in Eurasia and Africa. In all cases, the position of the epidemic front advanced exponentially with time, and epidemic velocity increased linearly with distance; regression slopes varied over a relatively narrow range among data sets. Estimates of the inverse power law exponent for dispersal that would be required to attain the rates of disease spread observed in the field also varied relatively little (1.74-2.36), despite more than a fivefold range of spatial scale among the data sets.

Aerial dispersal and multiple-scale spread of epidemic disease.

Disease spread has traditionally been described as a traveling wave of constant velocity. However, aerially dispersed pathogens capable of long-distance dispersal often have dispersal gradients with extended tails that could result in acceleration of the epidemic front. We evaluated empirical data with a simple model of disease spread that incorporates logistic growth in time with an inverse power function for dispersal. The scale invariance of the power law dispersal function implies its applicability at any spatial scale; indeed, the model successfully described epidemics ranging over six orders of magnitude, from experimental field plots to continental-scale epidemics of both plant and animal diseases. The distance traveled by epidemic fronts approximately doubled per unit time, velocity increased linearly with distance (slope ~(1/2)), and the exponent of the inverse power law was approximately 2. We found that it also may be possible to scale epidemics to account for initial outbreak focus size and the frequency of susceptible hosts. These relationships improve understanding of the geographic spread of emerging diseases, and facilitate the development of methods for predicting and preventing epidemics of plants, animals, and humans caused by pathogens that are capable of long-distance dispersal.

Primary disease gradients of wheat stripe rust in large field plots.

ABSTRACT Field data on disease gradients are essential for understanding the spread of plant diseases. In particular, dispersal far from an inoculum source can drive the behavior of an expanding focal epidemic. In this study, primary disease gradients of wheat stripe rust, caused by the aerially dispersed fungal pathogen Puccinia striiformis, were measured in Madras and Hermiston, OR, in the spring of 2002 and 2003. Plots were 6.1 m wide by 128 to 171 m long, and inoculated with urediniospores in an area of 1.52 by 1.52 m. Gradients were measured as far as 79.2 m downwind and 12.2 m upwind of the focus. Four gradient models-the power law, the modified power law, the exponential model, and the Lambert's general model-were fit to the data. Five of eight gradients were better fit by the power law, modified power law, and Lambert model than by the exponential, revealing the non-exponentially bound nature of the gradient tails. The other three data sets, which comprised fewer data points, were fit equally well by all the models. By truncating the largest data sets (maximum distances 79.2, 48.8, and 30.5 m) to within 30.5, 18.3, and 6.1 m of the focus, it was shown how the relative suitability of dispersal models can be obscured when data are available only at a short distance from the focus. The truncated data sets were also used to examine the danger associated with extrapolating gradients to distances beyond available data. The power law and modified power law predicted dispersal at large distances well relative to the Lambert and exponential models, which consistently and sometimes severely underestimated dispersal at large distances.

The effects of dispersal gradient and pathogen life cycle components on epidemic velocity in computer simulations.

ABSTRACT The velocity of expansion of focal epidemics was studied using an updated version of the simulation model EPIMUL, with model parameters relevant to wheat stripe rust. The modified power law, the exponential model, and Lambert's general model were fit to primary disease gradient data from an artificially initiated field epidemic of stripe rust and employed to describe dispersal in simulations. The exponential model, which fit the field data poorly (R (2) = 0.728 to 0.776), yielded an epidemic that expanded as a traveling wave (i.e., at a constant velocity), after an initial buildup period. Both the modified power law and the Lambert model fit the field data well (R(2) = 0.962 to 0.988) and resulted in dispersive epidemic waves (velocities increased over time for the entire course of the epidemic). The field epidemic also expanded as a dispersive wave. Using parameters based on the field epidemic and modified power law dispersal as a baseline, life cycle components of the pathogen (lesion growth rate, latent period, infectious period, and multiplication rate) and dispersal gradient steepness were varied within biologically reasonable ranges for this disease to test their effect on dispersive wave epidemics. All components but the infectious period had a strong influence on epidemic velocity, but none changed the general pattern of velocity increasing over time.